Signal processing systems generally include a number of components that perform a series of signal operations and transformations to one or more input signals in order to obtain a set of desired output signals. In most real world applications, such signal processing systems are required to carry out the processing in real time to produce samples of the output signals as samples of the input signals become available. This processing can be carried out using sample-based processing or frame-based processing. In sample-based processing, each component acts upon one sample of its input signal every time it executes. In frame-based processing, each component acts upon a batch or “frame” of contiguous samples in its input signal every time it executes.
Frame-based processing has some advantages over sample-based processing. For example, frame-based processing decreases the number of times components execute in order to process a given number of samples. This reduction decreases the overhead involved in repeatedly executing components within the system both in software and hardware implementations of the overall system.
Also with frame-based processing there are a variety of signal operations and transformations that have more efficient algorithmic implementations when more than one sample is processed at each execution step of the algorithm. An example of such an operation is Finite Impulse Response (FIR) digital filtering which can be implemented either through a direct sample-based convolution or through the frame-based Overlap-Add (OLA) algorithm. For N samples of the input signal processed through an M-tap filter, the direct convolution approach has a computational complexity of O(NM), while the OLA algorithm has a superior computational complexity of O(N log M).
Block-diagram modeling simplifies the process of conceptualizing, designing, simulating, and implementing (in software or hardware) custom signal processing systems. Block-diagram models are time-based relationships between signals and state variables representative of a dynamic system. The solution (computation of system response) of the model is obtained by evaluating these relationships over time, where time starts at a user-specified “start time” and ends at a user-specified “stop time”. Each evaluation of these relationships is referred to as a time step. Signals represent quantities that change over time, and these quantities are defined for all points in time between the block-diagram's start and stop time. The relationships between signals and state variables are defined by sets of equations represented by blocks. These equations define a relationship between the input signals, output signals, and state variables. Inherent in the definition is the notion of parameters, which are the coefficients of the equations. The block-diagram modeling approach has spawned a variety of software products such as Simulink® that cater to various aspects of system analysis and design.
A signal is said to be sample-based when its value is represented by a single sample. Extending this notion, a signal is frame-based when its value is represented by a batch of multiple samples.